sandeep-krishnamurthy closed pull request #46: Removed torch.html and all its references. Fixed Nesterov Momentum education ? URL: https://github.com/apache/incubator-mxnet-site/pull/46
This is a PR merged from a forked repository. As GitHub hides the original diff on merge, it is displayed below for the sake of provenance: As this is a foreign pull request (from a fork), the diff is supplied below (as it won't show otherwise due to GitHub magic): diff --git a/_modules/mxnet/optimizer.html b/_modules/mxnet/optimizer.html index ec3ead4c..9b29ac84 100644 --- a/_modules/mxnet/optimizer.html +++ b/_modules/mxnet/optimizer.html @@ -1267,7 +1267,7 @@ <h1>Source code for mxnet.optimizer</h1><div class="highlight"><pre> <span class="sd"> Much like Adam is essentially RMSprop with momentum,</span> <span class="sd"> Nadam is Adam RMSprop with Nesterov momentum available</span> -<span class="sd"> at http://cs229.stanford.edu/proj2015/054_report.pdf.</span> +<span class="sd"> at https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ.</span> <span class="sd"> This optimizer accepts the following parameters in addition to those accepted</span> <span class="sd"> by :class:`.Optimizer`.</span> diff --git a/api/python/model.html b/api/python/model.html index 321daa14..bd9979b7 100644 --- a/api/python/model.html +++ b/api/python/model.html @@ -2187,7 +2187,7 @@ <h1 id="logo-wrap"> <dd><p>The Nesterov Adam optimizer.</p> <p>Much like Adam is essentially RMSprop with momentum, Nadam is Adam RMSprop with Nesterov momentum available -at <a class="reference external" href="http://cs229.stanford.edu/proj2015/054_report.pdf";>http://cs229.stanford.edu/proj2015/054_report.pdf</a>.</p> +at <a class="reference external" href="https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ";>https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ</a>.</p> <p>This optimizer accepts the following parameters in addition to those accepted by <a class="reference internal" href="optimization/optimization.html#mxnet.optimizer.Optimizer" title="mxnet.optimizer.Optimizer"><code class="xref py py-class docutils literal"><span class="pre">Optimizer</span></code></a>.</p> <table class="docutils field-list" frame="void" rules="none"> diff --git a/api/python/optimization.html b/api/python/optimization.html index bb8cf9c6..3c563e60 100644 --- a/api/python/optimization.html +++ b/api/python/optimization.html @@ -811,7 +811,7 @@ <h1 id="logo-wrap"> <dd><p>The Nesterov Adam optimizer.</p> <p>Much like Adam is essentially RMSprop with momentum, Nadam is Adam RMSprop with Nesterov momentum available -at <a class="reference external" href="http://cs229.stanford.edu/proj2015/054_report.pdf";>http://cs229.stanford.edu/proj2015/054_report.pdf</a>.</p> +at <a class="reference external" href="https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ";>https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ</a>.</p> <p>This optimizer accepts the following parameters in addition to those accepted by <a class="reference internal" href="#mxnet.optimizer.Optimizer" title="mxnet.optimizer.Optimizer"><code class="xref py py-class docutils literal"><span class="pre">Optimizer</span></code></a>.</p> <table class="docutils field-list" frame="void" rules="none"> diff --git a/api/python/optimization/optimization.html b/api/python/optimization/optimization.html index 03e4c76b..4fb684e1 100644 --- a/api/python/optimization/optimization.html +++ b/api/python/optimization/optimization.html @@ -978,7 +978,7 @@ <h1 id="logo-wrap"> <dd><p>The Nesterov Adam optimizer.</p> <p>Much like Adam is essentially RMSprop with momentum, Nadam is Adam RMSprop with Nesterov momentum available -at <a class="reference external" href="http://cs229.stanford.edu/proj2015/054_report.pdf";>http://cs229.stanford.edu/proj2015/054_report.pdf</a>.</p> +at <a class="reference external" href="https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ";>https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ</a>.</p> <p>This optimizer accepts the following parameters in addition to those accepted by <a class="reference internal" href="#mxnet.optimizer.Optimizer" title="mxnet.optimizer.Optimizer"><code class="xref py py-class docutils literal"><span class="pre">Optimizer</span></code></a>.</p> <table class="docutils field-list" frame="void" rules="none"> diff --git a/faq/develop_and_hack.html b/faq/develop_and_hack.html index b105ca99..1f068729 100644 --- a/faq/develop_and_hack.html +++ b/faq/develop_and_hack.html @@ -207,7 +207,6 @@ <h1 id="logo-wrap"> <div class="toctree-wrapper compound"> <ul> <li class="toctree-l1"><a class="reference internal" href="new_op.html">Create new operators</a></li> -<li class="toctree-l1"><a class="reference internal" href="torch.html">Use Torch from MXNet</a></li> <li class="toctree-l1"><a class="reference internal" href="env_var.html">Set environment variables of MXNet</a></li> </ul> </div> diff --git a/faq/index.html b/faq/index.html index aedc70fd..c74d9f6c 100644 --- a/faq/index.html +++ b/faq/index.html @@ -229,7 +229,6 @@ <h1 id="logo-wrap"> <li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/add_op_in_backend.html";>How do I implement operators in MXNet backend?</a></li> <li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/new_op.html";>How do I create new operators in MXNet?</a></li> <li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/env_var.html";>How do I set MXNet?s environmental variables?</a></li> -<li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/torch.html";>How do I use MXNet as a front end for Torch?</a></li> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="#questions-about-using-mxnet">Questions about Using MXNet</a></li> @@ -303,7 +302,6 @@ <h1 id="logo-wrap"> <li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/add_op_in_backend.html";>How do I implement operators in MXNet backend?</a></li> <li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/new_op.html";>How do I create new operators in MXNet?</a></li> <li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/env_var.html";>How do I set MXNet?s environmental variables?</a></li> -<li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/torch.html";>How do I use MXNet as a front end for Torch?</a></li> </ul> </div> </div> diff --git a/faq/torch.html b/faq/torch.html deleted file mode 100644 index f3553a0c..00000000 --- a/faq/torch.html +++ /dev/null @@ -1,315 +0,0 @@ -<!DOCTYPE html> - -<html lang="en"> -<head> -<meta charset="utf-8"/> -<meta content="IE=edge" http-equiv="X-UA-Compatible"/> -<meta content="width=device-width, initial-scale=1" name="viewport"/> -<title>How to Use MXNet As an (Almost) Full-function Torch Front End ? mxnet documentation</title> -<link crossorigin="anonymous" 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id="how-to-use-mxnet-as-an-almost-full-function-torch-front-end"></span><h1>How to Use MXNet As an (Almost) Full-function Torch Front End<a class="headerlink" href="#how-to-use-mxnet-as-an-almost-full-function-torch-front-end" title="Permalink to this headline">?</a></h1> -<p>This topic demonstrates how to use MXNet as a front end to two of Torch?s major functionalities:</p> -<ul class="simple"> -<li>Call Torch?s tensor mathematical functions with MXNet.NDArray</li> -<li>Embed Torch?s neural network modules (layers) into MXNet?s symbolic graph</li> -</ul> -<div class="section" id="compile-with-torch"> -<span id="compile-with-torch"></span><h2>Compile with Torch<a class="headerlink" href="#compile-with-torch" title="Permalink to this headline">?</a></h2> -<ul class="simple"> -<li>Install Torch using the <a class="reference external" href="http://torch.ch/docs/getting-started.html";>official guide</a>.<ul> -<li>If you haven?t already done so, copy <code class="docutils literal"><span class="pre">make/config.mk</span></code> (Linux) or <code class="docutils literal"><span class="pre">make/osx.mk</span></code> (Mac) into the MXNet root folder as <code class="docutils literal"><span class="pre">config.mk</span></code>. In <code class="docutils literal"><span class="pre">config.mk</span></code> uncomment the lines <code class="docutils literal"><span class="pre">TORCH_PATH</span> <span class="pre">=</span> <span class="pre">$(HOME)/torch</span></code> and <code class="docutils literal"><span class="pre">MXNET_PLUGINS</span> <span class="pre">+=</span> <span class="pre">plugin/torch/torch.mk</span></code>.</li> -<li>By default, Torch should be installed in your home folder (so <code class="docutils literal"><span class="pre">TORCH_PATH</span> <span class="pre">=</span> <span class="pre">$(HOME)/torch</span></code>). Modify TORCH_PATH to point to your torch installation, if necessary.</li> -</ul> -</li> -<li>Run <code class="docutils literal"><span class="pre">make</span> <span class="pre">clean</span> <span class="pre">&&</span> <span class="pre">make</span></code> to build MXNet with Torch support.</li> -</ul> -</div> -<div class="section" id="tensor-mathematics"> -<span id="tensor-mathematics"></span><h2>Tensor Mathematics<a class="headerlink" href="#tensor-mathematics" title="Permalink to this headline">?</a></h2> -<p>The mxnet.th module supports calling Torch?s tensor mathematical functions with mxnet.nd.NDArray. See <a class="reference external" href="https://github.com/dmlc/mxnet/blob/master/example/torch/torch_function.py";>complete code</a>:</p> -<div class="highlight-python"><div class="highlight"><pre><span></span> <span class="kn">import</span> <span class="nn">mxnet</span> <span class="kn">as</span> <span class="nn">mx</span> - <span class="n">x</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">th</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="n">ctx</span><span class="o">=</span><span class="n">mx</span><span class="o">.</span><span class="n">cpu</span><span class="p">(</span><span class="mi">0</span><span class="p">))</span> - <span class="k">print</span> <span class="n">x</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">()</span> - <span class="n">y</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">th</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> - <span class="k">print</span> <span class="n">y</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">()</span> - - <span class="n">x</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">th</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="n">ctx</span><span class="o">=</span><span class="n">mx</span><span class="o">.</span><span class="n">cpu</span><span class="p">(</span><span class="mi">0</span><span class="p">))</span> - <span class="k">print</span> <span class="n">x</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">()</span> - <span class="n">mx</span><span class="o">.</span><span class="n">th</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">x</span><span class="p">)</span> <span class="c1"># in-place</span> - <span class="k">print</span> <span class="n">x</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">()</span> -</pre></div> -</div> -<p>For help, use the <code class="docutils literal"><span class="pre">help(mx.th)</span></code> command.</p> -<p>We?ve added support for most common functions listed on <a class="reference external" href="https://github.com/torch/torch7/blob/master/doc/maths.md";>Torch?s documentation page</a>. -If you find that the function you need is not supported, you can easily register it in <code class="docutils literal"><span class="pre">mxnet_root/plugin/torch/torch_function.cc</span></code> by using the existing registrations as examples.</p> -</div> -<div class="section" id="torch-modules-layers"> -<span id="torch-modules-layers"></span><h2>Torch Modules (Layers)<a class="headerlink" href="#torch-modules-layers" title="Permalink to this headline">?</a></h2> -<p>MXNet supports Torch?s neural network modules through the<code class="docutils literal"><span class="pre">mxnet.symbol.TorchModule</span></code> symbol. -For example, the following code defines a three-layer DNN for classifying MNIST digits (<a class="reference external" href="https://github.com/dmlc/mxnet/blob/master/example/torch/torch_module.py";>full code</a>):</p> -<div class="highlight-python"><div class="highlight"><pre><span></span> <span class="n">data</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">symbol</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="s1">'data'</span><span class="p">)</span> - <span class="n">fc1</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">symbol</span><span class="o">.</span><span class="n">TorchModule</span><span class="p">(</span><span class="n">data_0</span><span class="o">=</span><span class="n">data</span><span class="p">,</span> <span class="n">lua_string</span><span class="o">=</span><span class="s1">'nn.Linear(784, 128)'</span><span class="p">,</span> <span class="n">num_data</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">num_params</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">num_outputs</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">'fc1'</span><span class="p">)</span> - <span class="n">act1</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">symbol</span><span class="o">.</span><span class="n">TorchModule</span><span class="p">(</span><span class="n">data_0</span><span class="o">=</span><span class="n">fc1</span><span class="p">,</span> <span class="n">lua_string</span><span class="o">=</span><span class="s1">'nn.ReLU(false)'</span><span class="p">,</span> <span class="n">num_data</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">num_params</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">num_outputs</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">'relu1'</span><span class="p">)</span> - <span class="n">fc2</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">symbol</span><span class="o">.</span><span class="n">TorchModule</span><span class="p">(</span><span class="n">data_0</span><span class="o">=</span><span class="n">act1</span><span class="p">,</span> <span class="n">lua_string</span><span class="o">=</span><span class="s1">'nn.Linear(128, 64)'</span><span class="p">,</span> <span class="n">num_data</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">num_params</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">num_outputs</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">'fc2'</span><span class="p">)</span> - <span class="n">act2</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">symbol</span><span class="o">.</span><span class="n">TorchModule</span><span class="p">(</span><span class="n">data_0</span><span class="o">=</span><span class="n">fc2</span><span class="p">,</span> <span class="n">lua_string</span><span class="o">=</span><span class="s1">'nn.ReLU(false)'</span><span class="p">,</span> <span class="n">num_data</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">num_params</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">num_outputs</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">'relu2'</span><span class="p">)</span> - <span class="n">fc3</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">symbol</span><span class="o">.</span><span class="n">TorchModule</span><span class="p">(</span><span class="n">data_0</span><span class="o">=</span><span class="n">act2</span><span class="p">,</span> <span class="n">lua_string</span><span class="o">=</span><span class="s1">'nn.Linear(64, 10)'</span><span class="p">,</span> <span class="n">num_data</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">num_params</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">num_outputs</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">'fc3'</span><span class="p">)</span> - <span class="n">mlp</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">symbol</span><span class="o">.</span><span class="n">SoftmaxOutput</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">fc3</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">'softmax'</span><span class="p">)</span> -</pre></div> -</div> -<p>Let?s break it down. First <code class="docutils literal"><span class="pre">data</span> <span class="pre">=</span> <span class="pre">mx.symbol.Variable('data')</span></code> defines a Variable as a placeholder for input. -Then, it?s fed through Torch?s nn modules with: -<code class="docutils literal"><span class="pre">fc1</span> <span class="pre">=</span> <span class="pre">mx.symbol.TorchModule(data_0=data,</span> <span class="pre">lua_string='nn.Linear(784,</span> <span class="pre">128)',</span> <span class="pre">num_data=1,</span> <span class="pre">num_params=2,</span> <span class="pre">num_outputs=1,</span> <span class="pre">name='fc1')</span></code>. -To use Torch?s criterion as loss functions, you can replace the last line with:</p> -<div class="highlight-python"><div class="highlight"><pre><span></span> <span class="n">logsoftmax</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">symbol</span><span class="o">.</span><span class="n">TorchModule</span><span class="p">(</span><span class="n">data_0</span><span class="o">=</span><span class="n">fc3</span><span class="p">,</span> <span class="n">lua_string</span><span class="o">=</span><span class="s1">'nn.LogSoftMax()'</span><span class="p">,</span> <span class="n">num_data</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">num_params</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">num_outputs</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">'logsoftmax'</span><span class="p">)</span> - <span class="c1"># Torch's label starts from 1</span> - <span class="n">label</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">symbol</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="s1">'softmax_label'</span><span class="p">)</span> <span class="o">+</span> <span class="mi">1</span> - <span class="n">mlp</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">symbol</span><span class="o">.</span><span class="n">TorchCriterion</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">logsoftmax</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="n">label</span><span class="p">,</span> <span class="n">lua_string</span><span class="o">=</span><span class="s1">'nn.ClassNLLCriterion()'</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">'softmax'</span><span class="p">)</span> -</pre></div> -</div> -<p>The input to the nn module is named data_i for i = 0 ... num_data-1. <code class="docutils literal"><span class="pre">lua_string</span></code> is a single Lua statement that creates the module object. -For Torch?s built-in module, this is simply <code class="docutils literal"><span class="pre">nn.module_name(arguments)</span></code>. -If you are using a custom module, place it in a .lua script file and load it with <code class="docutils literal"><span class="pre">require</span> <span class="pre">'module_file.lua'</span></code> if your script returns a torch.nn object, or <code class="docutils literal"><span class="pre">(require</span> <span class="pre">'module_file.lua')()</span></code> if your script returns a torch.nn class.</p> -</div> -</div> -</div> -</div> -<div aria-label="main navigation" class="sphinxsidebar rightsidebar" role="navigation"> -<div class="sphinxsidebarwrapper"> -<h3><a href="../index.html">Table Of Contents</a></h3> -<ul> -<li><a class="reference internal" href="#">How to Use MXNet As an (Almost) Full-function Torch Front End</a><ul> -<li><a class="reference internal" href="#compile-with-torch">Compile with Torch</a></li> -<li><a class="reference internal" href="#tensor-mathematics">Tensor Mathematics</a></li> -<li><a class="reference internal" href="#torch-modules-layers">Torch Modules (Layers)</a></li> -</ul> -</li> -</ul> -</div> -</div> -</div><div class="footer"> -<div class="section-disclaimer"> -<div class="container"> -<div> -<img height="60" src="https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/image/apache_incubator_logo.png"/> -<p> - Apache MXNet is an effort undergoing incubation at The Apache Software Foundation (ASF), <strong>sponsored by the <i>Apache Incubator</i></strong>. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF. - </p> -<p> - "Copyright ? 2017, The Apache Software Foundation - Apache MXNet, MXNet, Apache, the Apache feather, and the Apache MXNet project logo are either registered trademarks or trademarks of the Apache Software Foundation." - </p> -</div> -</div> -</div> -</div> <!-- pagename != index --> -</div> -<script crossorigin="anonymous" integrity="sha384-0mSbJDEHialfmuBBQP6A4Qrprq5OVfW37PRR3j5ELqxss1yVqOtnepnHVP9aJ7xS" src="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.6/js/bootstrap.min.js";></script> -<script src="../_static/js/sidebar.js" type="text/javascript"></script> -<script src="../_static/js/search.js" type="text/javascript"></script> -<script src="../_static/js/navbar.js" type="text/javascript"></script> -<script src="../_static/js/clipboard.min.js" type="text/javascript"></script> -<script src="../_static/js/copycode.js" type="text/javascript"></script> -<script src="../_static/js/page.js" type="text/javascript"></script> -<script type="text/javascript"> - $('body').ready(function () { - $('body').css('visibility', 'visible'); - }); - </script> -</body> -</html> \ No newline at end of file diff --git a/how_to/develop_and_hack.html b/how_to/develop_and_hack.html index ddc5aa9c..bbb4c1d7 100644 --- a/how_to/develop_and_hack.html +++ b/how_to/develop_and_hack.html @@ -169,7 +169,6 @@ <h1 id="logo-wrap"> <div class="toctree-wrapper compound"> <ul> <li class="toctree-l1"><a class="reference internal" href="new_op.html">Create new operators</a></li> -<li class="toctree-l1"><a class="reference internal" href="torch.html">Use Torch from MXNet</a></li> <li class="toctree-l1"><a class="reference internal" href="env_var.html">Set environment variables of MXNet</a></li> </ul> </div> diff --git a/how_to/index.html b/how_to/index.html index 380d51cb..f88b0b62 100644 --- a/how_to/index.html +++ b/how_to/index.html @@ -188,7 +188,6 @@ <h1 id="logo-wrap"> <li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/community/contribute.html";>How do I contribute a patch to MXNet?</a></li> <li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/new_op.html";>How do I create new operators in MXNet?</a></li> <li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/env_var.html";>How do I set MXNet?s environmental variables?</a></li> -<li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/torch.html";>How do I use MXNet as a front end for Torch?</a></li> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="#questions-about-using-mxnet">Questions about Using MXNet</a></li> @@ -251,7 +250,6 @@ <h1 id="logo-wrap"> <li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/community/contribute.html";>How do I contribute a patch to MXNet?</a></li> <li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/new_op.html";>How do I create new operators in MXNet?</a></li> <li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/env_var.html";>How do I set MXNet?s environmental variables?</a></li> -<li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/torch.html";>How do I use MXNet as a front end for Torch?</a></li> </ul> </div> </div> diff --git a/how_to/torch.html b/how_to/torch.html deleted file mode 100644 index f69a78f8..00000000 --- a/how_to/torch.html +++ /dev/null @@ -1,264 +0,0 @@ -<!DOCTYPE html> - -<html lang="en"> -<head> -<meta charset="utf-8"/> -<meta content="IE=edge" http-equiv="X-UA-Compatible"/> -<meta content="width=device-width, initial-scale=1" name="viewport"/> 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id="how-to-use-mxnet-as-an-almost-full-function-torch-front-end"> -<span id="how-to-use-mxnet-as-an-almost-full-function-torch-front-end"></span><h1>How to Use MXNet As an (Almost) Full-function Torch Front End<a class="headerlink" href="#how-to-use-mxnet-as-an-almost-full-function-torch-front-end" title="Permalink to this headline">?</a></h1> -<p>This topic demonstrates how to use MXNet as a front end to two of Torch?s major functionalities:</p> -<ul class="simple"> -<li>Call Torch?s tensor mathematical functions with MXNet.NDArray</li> -<li>Embed Torch?s neural network modules (layers) into MXNet?s symbolic graph</li> -</ul> -<div class="section" id="compile-with-torch"> -<span id="compile-with-torch"></span><h2>Compile with Torch<a class="headerlink" href="#compile-with-torch" title="Permalink to this headline">?</a></h2> -<ul class="simple"> -<li>Install Torch using the <a class="reference external" href="http://torch.ch/docs/getting-started.html";>official guide</a>.<ul> -<li>If you haven?t already done so, copy <code class="docutils literal"><span class="pre">make/config.mk</span></code> (Linux) or <code class="docutils literal"><span class="pre">make/osx.mk</span></code> (Mac) into the MXNet root folder as <code class="docutils literal"><span class="pre">config.mk</span></code>. In <code class="docutils literal"><span class="pre">config.mk</span></code> uncomment the lines <code class="docutils literal"><span class="pre">TORCH_PATH</span> <span class="pre">=</span> <span class="pre">$(HOME)/torch</span></code> and <code class="docutils literal"><span class="pre">MXNET_PLUGINS</span> <span class="pre">+=</span> <span class="pre">plugin/torch/torch.mk</span></code>.</li> -<li>By default, Torch should be installed in your home folder (so <code class="docutils literal"><span class="pre">TORCH_PATH</span> <span class="pre">=</span> <span class="pre">$(HOME)/torch</span></code>). Modify TORCH_PATH to point to your torch installation, if necessary.</li> -</ul> -</li> -<li>Run <code class="docutils literal"><span class="pre">make</span> <span class="pre">clean</span> <span class="pre">&&</span> <span class="pre">make</span></code> to build MXNet with Torch support.</li> -</ul> -</div> -<div class="section" id="tensor-mathematics"> -<span id="tensor-mathematics"></span><h2>Tensor Mathematics<a class="headerlink" href="#tensor-mathematics" title="Permalink to this headline">?</a></h2> -<p>The mxnet.th module supports calling Torch?s tensor mathematical functions with mxnet.nd.NDArray. See <a class="reference external" href="https://github.com/dmlc/mxnet/blob/master/example/torch/torch_function.py";>complete code</a>:</p> -<div class="highlight-python"><div class="highlight"><pre><span></span> <span class="kn">import</span> <span class="nn">mxnet</span> <span class="kn">as</span> <span class="nn">mx</span> - <span class="n">x</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">th</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="n">ctx</span><span class="o">=</span><span class="n">mx</span><span class="o">.</span><span class="n">cpu</span><span class="p">(</span><span class="mi">0</span><span class="p">))</span> - <span class="k">print</span> <span class="n">x</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">()</span> - <span class="n">y</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">th</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> - <span class="k">print</span> <span class="n">y</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">()</span> - - <span class="n">x</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">th</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="n">ctx</span><span class="o">=</span><span class="n">mx</span><span class="o">.</span><span class="n">cpu</span><span class="p">(</span><span class="mi">0</span><span class="p">))</span> - <span class="k">print</span> <span class="n">x</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">()</span> - <span class="n">mx</span><span class="o">.</span><span class="n">th</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">x</span><span class="p">)</span> <span class="c1"># in-place</span> - <span class="k">print</span> <span class="n">x</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">()</span> -</pre></div> -</div> -<p>For help, use the <code class="docutils literal"><span class="pre">help(mx.th)</span></code> command.</p> -<p>We?ve added support for most common functions listed on <a class="reference external" href="https://github.com/torch/torch7/blob/master/doc/maths.md";>Torch?s documentation page</a>. -If you find that the function you need is not supported, you can easily register it in <code class="docutils literal"><span class="pre">mxnet_root/plugin/torch/torch_function.cc</span></code> by using the existing registrations as examples.</p> -</div> -<div class="section" id="torch-modules-layers"> -<span id="torch-modules-layers"></span><h2>Torch Modules (Layers)<a class="headerlink" href="#torch-modules-layers" title="Permalink to this headline">?</a></h2> -<p>MXNet supports Torch?s neural network modules through the<code class="docutils literal"><span class="pre">mxnet.symbol.TorchModule</span></code> symbol. -For example, the following code defines a three-layer DNN for classifying MNIST digits (<a class="reference external" href="https://github.com/dmlc/mxnet/blob/master/example/torch/torch_module.py";>full code</a>):</p> -<div class="highlight-python"><div class="highlight"><pre><span></span> <span class="n">data</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">symbol</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="s1">'data'</span><span class="p">)</span> - <span class="n">fc1</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">symbol</span><span class="o">.</span><span class="n">TorchModule</span><span class="p">(</span><span class="n">data_0</span><span class="o">=</span><span class="n">data</span><span class="p">,</span> <span class="n">lua_string</span><span class="o">=</span><span class="s1">'nn.Linear(784, 128)'</span><span class="p">,</span> <span class="n">num_data</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">num_params</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">num_outputs</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">'fc1'</span><span class="p">)</span> - <span class="n">act1</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">symbol</span><span class="o">.</span><span class="n">TorchModule</span><span class="p">(</span><span class="n">data_0</span><span class="o">=</span><span class="n">fc1</span><span class="p">,</span> <span class="n">lua_string</span><span class="o">=</span><span class="s1">'nn.ReLU(false)'</span><span class="p">,</span> <span class="n">num_data</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">num_params</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">num_outputs</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">'relu1'</span><span class="p">)</span> - <span class="n">fc2</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">symbol</span><span class="o">.</span><span class="n">TorchModule</span><span class="p">(</span><span class="n">data_0</span><span class="o">=</span><span class="n">act1</span><span class="p">,</span> <span class="n">lua_string</span><span class="o">=</span><span class="s1">'nn.Linear(128, 64)'</span><span class="p">,</span> <span class="n">num_data</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">num_params</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">num_outputs</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">'fc2'</span><span class="p">)</span> - <span class="n">act2</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">symbol</span><span class="o">.</span><span class="n">TorchModule</span><span class="p">(</span><span class="n">data_0</span><span class="o">=</span><span class="n">fc2</span><span class="p">,</span> <span class="n">lua_string</span><span class="o">=</span><span class="s1">'nn.ReLU(false)'</span><span class="p">,</span> <span class="n">num_data</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">num_params</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">num_outputs</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">'relu2'</span><span class="p">)</span> - <span class="n">fc3</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">symbol</span><span class="o">.</span><span class="n">TorchModule</span><span class="p">(</span><span class="n">data_0</span><span class="o">=</span><span class="n">act2</span><span class="p">,</span> <span class="n">lua_string</span><span class="o">=</span><span class="s1">'nn.Linear(64, 10)'</span><span class="p">,</span> <span class="n">num_data</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">num_params</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">num_outputs</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">'fc3'</span><span class="p">)</span> - <span class="n">mlp</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">symbol</span><span class="o">.</span><span class="n">SoftmaxOutput</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">fc3</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">'softmax'</span><span class="p">)</span> -</pre></div> -</div> -<p>Let?s break it down. First <code class="docutils literal"><span class="pre">data</span> <span class="pre">=</span> <span class="pre">mx.symbol.Variable('data')</span></code> defines a Variable as a placeholder for input. -Then, it?s fed through Torch?s nn modules with: -<code class="docutils literal"><span class="pre">fc1</span> <span class="pre">=</span> <span class="pre">mx.symbol.TorchModule(data_0=data,</span> <span class="pre">lua_string='nn.Linear(784,</span> <span class="pre">128)',</span> <span class="pre">num_data=1,</span> <span class="pre">num_params=2,</span> <span class="pre">num_outputs=1,</span> <span class="pre">name='fc1')</span></code>. -To use Torch?s criterion as loss functions, you can replace the last line with:</p> -<div class="highlight-python"><div class="highlight"><pre><span></span> <span class="n">logsoftmax</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">symbol</span><span class="o">.</span><span class="n">TorchModule</span><span class="p">(</span><span class="n">data_0</span><span class="o">=</span><span class="n">fc3</span><span class="p">,</span> <span class="n">lua_string</span><span class="o">=</span><span class="s1">'nn.LogSoftMax()'</span><span class="p">,</span> <span class="n">num_data</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">num_params</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">num_outputs</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">'logsoftmax'</span><span class="p">)</span> - <span class="c1"># Torch's label starts from 1</span> - <span class="n">label</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">symbol</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="s1">'softmax_label'</span><span class="p">)</span> <span class="o">+</span> <span class="mi">1</span> - <span class="n">mlp</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">symbol</span><span class="o">.</span><span class="n">TorchCriterion</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">logsoftmax</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="n">label</span><span class="p">,</span> <span class="n">lua_string</span><span class="o">=</span><span class="s1">'nn.ClassNLLCriterion()'</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">'softmax'</span><span class="p">)</span> -</pre></div> -</div> -<p>The input to the nn module is named data_i for i = 0 ... num_data-1. <code class="docutils literal"><span class="pre">lua_string</span></code> is a single Lua statement that creates the module object. -For Torch?s built-in module, this is simply <code class="docutils literal"><span class="pre">nn.module_name(arguments)</span></code>. -If you are using a custom module, place it in a .lua script file and load it with <code class="docutils literal"><span class="pre">require</span> <span class="pre">'module_file.lua'</span></code> if your script returns a torch.nn object, or <code class="docutils literal"><span class="pre">(require</span> <span class="pre">'module_file.lua')()</span></code> if your script returns a torch.nn class.</p> -</div> -</div> -<div class="container"> -<div class="footer"> -<p> </p> -</div> -</div> -</div> -<div aria-label="main navigation" class="sphinxsidebar rightsidebar" role="navigation"> -<div class="sphinxsidebarwrapper"> -<h3><a href="../index.html">Table Of Contents</a></h3> -<ul> -<li><a class="reference internal" href="#">How to Use MXNet As an (Almost) Full-function Torch Front End</a><ul> -<li><a class="reference internal" href="#compile-with-torch">Compile with Torch</a></li> -<li><a class="reference internal" href="#tensor-mathematics">Tensor Mathematics</a></li> -<li><a class="reference internal" href="#torch-modules-layers">Torch Modules (Layers)</a></li> -</ul> -</li> -</ul> -</div> -</div> -</div> <!-- pagename != index --> -<script crossorigin="anonymous" integrity="sha384-0mSbJDEHialfmuBBQP6A4Qrprq5OVfW37PRR3j5ELqxss1yVqOtnepnHVP9aJ7xS" src="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.6/js/bootstrap.min.js";></script> -<script src="../_static/js/sidebar.js" type="text/javascript"></script> -<script src="../_static/js/search.js" type="text/javascript"></script> -<script src="../_static/js/navbar.js" type="text/javascript"></script> -<script src="../_static/js/clipboard.min.js" type="text/javascript"></script> -<script src="../_static/js/copycode.js" type="text/javascript"></script> -<script type="text/javascript"> - $('body').ready(function () { - $('body').css('visibility', 'visible'); - }); - </script> -</div></body> -</html> diff --git a/versions/0.11.0/api/python/model.html b/versions/0.11.0/api/python/model.html index fc1d1247..ba1dc53d 100644 --- a/versions/0.11.0/api/python/model.html +++ b/versions/0.11.0/api/python/model.html @@ -1966,7 +1966,7 @@ <h1 id="logo-wrap"> <dd><p>The Nesterov Adam optimizer.</p> <p>Much like Adam is essentially RMSprop with momentum, Nadam is Adam RMSprop with Nesterov momentum available -at <a class="reference external" href="http://cs229.stanford.edu/proj2015/054_report.pdf";>http://cs229.stanford.edu/proj2015/054_report.pdf</a>.</p> +at <a class="reference external" href="https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ";>https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ</a>.</p> <p>This optimizer accepts the following parameters in addition to those accepted by <a class="reference internal" href="optimization.html#mxnet.optimizer.Optimizer" title="mxnet.optimizer.Optimizer"><code class="xref py py-class docutils literal"><span class="pre">Optimizer</span></code></a>.</p> <table class="docutils field-list" frame="void" rules="none"> diff --git a/versions/0.11.0/api/python/optimization.html b/versions/0.11.0/api/python/optimization.html index 52d6e1de..1abc12e0 100644 --- a/versions/0.11.0/api/python/optimization.html +++ b/versions/0.11.0/api/python/optimization.html @@ -811,7 +811,7 @@ <h1 id="logo-wrap"> <dd><p>The Nesterov Adam optimizer.</p> <p>Much like Adam is essentially RMSprop with momentum, Nadam is Adam RMSprop with Nesterov momentum available -at <a class="reference external" href="http://cs229.stanford.edu/proj2015/054_report.pdf";>http://cs229.stanford.edu/proj2015/054_report.pdf</a>.</p> +at <a class="reference external" href="https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ";>https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ</a>.</p> <p>This optimizer accepts the following parameters in addition to those accepted by <a class="reference internal" href="#mxnet.optimizer.Optimizer" title="mxnet.optimizer.Optimizer"><code class="xref py py-class docutils literal"><span class="pre">Optimizer</span></code></a>.</p> <table class="docutils field-list" frame="void" rules="none"> diff --git a/versions/0.11.0/how_to/develop_and_hack.html b/versions/0.11.0/how_to/develop_and_hack.html index 7251e80f..2872dcb5 100644 --- a/versions/0.11.0/how_to/develop_and_hack.html +++ b/versions/0.11.0/how_to/develop_and_hack.html @@ -169,7 +169,6 @@ <h1 id="logo-wrap"> <div class="toctree-wrapper compound"> <ul> <li class="toctree-l1"><a class="reference internal" href="new_op.html">Create new operators</a></li> -<li class="toctree-l1"><a class="reference internal" href="torch.html">Use Torch from MXNet</a></li> <li class="toctree-l1"><a class="reference internal" href="env_var.html">Set environment variables of MXNet</a></li> </ul> </div> diff --git a/versions/0.11.0/how_to/index.html b/versions/0.11.0/how_to/index.html index 7b39bce0..237cafc8 100644 --- a/versions/0.11.0/how_to/index.html +++ b/versions/0.11.0/how_to/index.html @@ -188,7 +188,6 @@ <h1 id="logo-wrap"> <li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/community/contribute.html";>How do I contribute a patch to MXNet?</a></li> <li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/new_op.html";>How do I create new operators in MXNet?</a></li> <li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/env_var.html";>How do I set MXNet?s environmental variables?</a></li> -<li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/torch.html";>How do I use MXNet as a front end for Torch?</a></li> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="#questions-about-using-mxnet">Questions about Using MXNet</a></li> @@ -251,7 +250,6 @@ <h1 id="logo-wrap"> <li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/community/contribute.html";>How do I contribute a patch to MXNet?</a></li> <li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/new_op.html";>How do I create new operators in MXNet?</a></li> <li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/env_var.html";>How do I set MXNet?s environmental variables?</a></li> -<li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/torch.html";>How do I use MXNet as a front end for Torch?</a></li> </ul> </div> </div> diff --git a/versions/0.12.0/api/python/model.html b/versions/0.12.0/api/python/model.html index 1fbcaa53..c998ee65 100644 --- a/versions/0.12.0/api/python/model.html +++ b/versions/0.12.0/api/python/model.html @@ -2170,7 +2170,7 @@ <h1 id="logo-wrap"> <dd><p>The Nesterov Adam optimizer.</p> <p>Much like Adam is essentially RMSprop with momentum, Nadam is Adam RMSprop with Nesterov momentum available -at <a class="reference external" href="http://cs229.stanford.edu/proj2015/054_report.pdf";>http://cs229.stanford.edu/proj2015/054_report.pdf</a>.</p> +at <a class="reference external" href="https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ";>https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ</a>.</p> <p>This optimizer accepts the following parameters in addition to those accepted by <a class="reference internal" href="optimization/optimization.html#mxnet.optimizer.Optimizer" title="mxnet.optimizer.Optimizer"><code class="xref py py-class docutils literal"><span class="pre">Optimizer</span></code></a>.</p> <table class="docutils field-list" frame="void" rules="none"> diff --git a/versions/0.12.0/api/python/optimization.html b/versions/0.12.0/api/python/optimization.html index 800d05f0..b057f0c0 100644 --- a/versions/0.12.0/api/python/optimization.html +++ b/versions/0.12.0/api/python/optimization.html @@ -811,7 +811,7 @@ <h1 id="logo-wrap"> <dd><p>The Nesterov Adam optimizer.</p> <p>Much like Adam is essentially RMSprop with momentum, Nadam is Adam RMSprop with Nesterov momentum available -at <a class="reference external" href="http://cs229.stanford.edu/proj2015/054_report.pdf";>http://cs229.stanford.edu/proj2015/054_report.pdf</a>.</p> +at <a class="reference external" href="https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ";>https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ</a>.</p> <p>This optimizer accepts the following parameters in addition to those accepted by <a class="reference internal" href="#mxnet.optimizer.Optimizer" title="mxnet.optimizer.Optimizer"><code class="xref py py-class docutils literal"><span class="pre">Optimizer</span></code></a>.</p> <table class="docutils field-list" frame="void" rules="none"> diff --git a/versions/0.12.0/api/python/optimization/optimization.html b/versions/0.12.0/api/python/optimization/optimization.html index 75e4df51..3d761c19 100644 --- a/versions/0.12.0/api/python/optimization/optimization.html +++ b/versions/0.12.0/api/python/optimization/optimization.html @@ -961,7 +961,7 @@ <h1 id="logo-wrap"> <dd><p>The Nesterov Adam optimizer.</p> <p>Much like Adam is essentially RMSprop with momentum, Nadam is Adam RMSprop with Nesterov momentum available -at <a class="reference external" href="http://cs229.stanford.edu/proj2015/054_report.pdf";>http://cs229.stanford.edu/proj2015/054_report.pdf</a>.</p> +at <a class="reference external" href="https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ";>https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ</a>.</p> <p>This optimizer accepts the following parameters in addition to those accepted by <a class="reference internal" href="#mxnet.optimizer.Optimizer" title="mxnet.optimizer.Optimizer"><code class="xref py py-class docutils literal"><span class="pre">Optimizer</span></code></a>.</p> <table class="docutils field-list" frame="void" rules="none"> diff --git a/versions/0.12.0/faq/develop_and_hack.html b/versions/0.12.0/faq/develop_and_hack.html index e1aa7825..8393f576 100644 --- a/versions/0.12.0/faq/develop_and_hack.html +++ b/versions/0.12.0/faq/develop_and_hack.html @@ -207,7 +207,6 @@ <h1 id="logo-wrap"> <div class="toctree-wrapper compound"> <ul> <li class="toctree-l1"><a class="reference internal" href="new_op.html">Create new operators</a></li> -<li class="toctree-l1"><a class="reference internal" href="torch.html">Use Torch from MXNet</a></li> <li class="toctree-l1"><a class="reference internal" href="env_var.html">Set environment variables of MXNet</a></li> </ul> </div> diff --git a/versions/0.12.0/faq/index.html b/versions/0.12.0/faq/index.html index 40e9495e..8c997b11 100644 --- a/versions/0.12.0/faq/index.html +++ b/versions/0.12.0/faq/index.html @@ -225,7 +225,6 @@ <h1 id="logo-wrap"> <li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/add_op_in_backend.html";>How do I implement operators in MXNet backend?</a></li> <li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/new_op.html";>How do I create new operators in MXNet?</a></li> <li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/env_var.html";>How do I set MXNet?s environmental variables?</a></li> -<li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/torch.html";>How do I use MXNet as a front end for Torch?</a></li> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="#questions-about-using-mxnet">Questions about Using MXNet</a></li> @@ -291,7 +290,6 @@ <h1 id="logo-wrap"> <li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/add_op_in_backend.html";>How do I implement operators in MXNet backend?</a></li> <li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/new_op.html";>How do I create new operators in MXNet?</a></li> <li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/env_var.html";>How do I set MXNet?s environmental variables?</a></li> -<li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/torch.html";>How do I use MXNet as a front end for Torch?</a></li> </ul> </div> </div> diff --git a/versions/0.12.0/how_to/develop_and_hack.html b/versions/0.12.0/how_to/develop_and_hack.html index 267c6472..cd3b98b6 100644 --- a/versions/0.12.0/how_to/develop_and_hack.html +++ b/versions/0.12.0/how_to/develop_and_hack.html @@ -169,7 +169,6 @@ <h1 id="logo-wrap"> <div class="toctree-wrapper compound"> <ul> <li class="toctree-l1"><a class="reference internal" href="new_op.html">Create new operators</a></li> -<li class="toctree-l1"><a class="reference internal" href="torch.html">Use Torch from MXNet</a></li> <li class="toctree-l1"><a class="reference internal" href="env_var.html">Set environment variables of MXNet</a></li> </ul> </div> diff --git a/versions/0.12.0/how_to/index.html b/versions/0.12.0/how_to/index.html index de6c9258..7a75c635 100644 --- a/versions/0.12.0/how_to/index.html +++ b/versions/0.12.0/how_to/index.html @@ -188,7 +188,6 @@ <h1 id="logo-wrap"> <li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/community/contribute.html";>How do I contribute a patch to MXNet?</a></li> <li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/new_op.html";>How do I create new operators in MXNet?</a></li> <li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/env_var.html";>How do I set MXNet?s environmental variables?</a></li> -<li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/torch.html";>How do I use MXNet as a front end for Torch?</a></li> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="#questions-about-using-mxnet">Questions about Using MXNet</a></li> @@ -251,7 +250,6 @@ <h1 id="logo-wrap"> <li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/community/contribute.html";>How do I contribute a patch to MXNet?</a></li> <li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/new_op.html";>How do I create new operators in MXNet?</a></li> <li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/env_var.html";>How do I set MXNet?s environmental variables?</a></li> -<li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/torch.html";>How do I use MXNet as a front end for Torch?</a></li> </ul> </div> </div> diff --git a/versions/0.12.1/api/python/model.html b/versions/0.12.1/api/python/model.html index d9efe56c..73e8bced 100644 --- a/versions/0.12.1/api/python/model.html +++ b/versions/0.12.1/api/python/model.html @@ -2170,7 +2170,7 @@ <h1 id="logo-wrap"> <dd><p>The Nesterov Adam optimizer.</p> <p>Much like Adam is essentially RMSprop with momentum, Nadam is Adam RMSprop with Nesterov momentum available -at <a class="reference external" href="http://cs229.stanford.edu/proj2015/054_report.pdf";>http://cs229.stanford.edu/proj2015/054_report.pdf</a>.</p> +at <a class="reference external" href="https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ";>https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ</a>.</p> <p>This optimizer accepts the following parameters in addition to those accepted by <a class="reference internal" href="optimization/optimization.html#mxnet.optimizer.Optimizer" title="mxnet.optimizer.Optimizer"><code class="xref py py-class docutils literal"><span class="pre">Optimizer</span></code></a>.</p> <table class="docutils field-list" frame="void" rules="none"> diff --git a/versions/0.12.1/api/python/optimization.html b/versions/0.12.1/api/python/optimization.html index 3e6c6ae1..ee20509b 100644 --- a/versions/0.12.1/api/python/optimization.html +++ b/versions/0.12.1/api/python/optimization.html @@ -811,7 +811,7 @@ <h1 id="logo-wrap"> <dd><p>The Nesterov Adam optimizer.</p> <p>Much like Adam is essentially RMSprop with momentum, Nadam is Adam RMSprop with Nesterov momentum available -at <a class="reference external" href="http://cs229.stanford.edu/proj2015/054_report.pdf";>http://cs229.stanford.edu/proj2015/054_report.pdf</a>.</p> +at <a class="reference external" href="https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ";>https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ</a>.</p> <p>This optimizer accepts the following parameters in addition to those accepted by <a class="reference internal" href="#mxnet.optimizer.Optimizer" title="mxnet.optimizer.Optimizer"><code class="xref py py-class docutils literal"><span class="pre">Optimizer</span></code></a>.</p> <table class="docutils field-list" frame="void" rules="none"> diff --git a/versions/0.12.1/api/python/optimization/optimization.html b/versions/0.12.1/api/python/optimization/optimization.html index b6195786..e6e50a6a 100644 --- a/versions/0.12.1/api/python/optimization/optimization.html +++ b/versions/0.12.1/api/python/optimization/optimization.html @@ -961,7 +961,7 @@ <h1 id="logo-wrap"> <dd><p>The Nesterov Adam optimizer.</p> <p>Much like Adam is essentially RMSprop with momentum, Nadam is Adam RMSprop with Nesterov momentum available -at <a class="reference external" href="http://cs229.stanford.edu/proj2015/054_report.pdf";>http://cs229.stanford.edu/proj2015/054_report.pdf</a>.</p> +at <a class="reference external" href="https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ";>https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ</a>.</p> <p>This optimizer accepts the following parameters in addition to those accepted by <a class="reference internal" href="#mxnet.optimizer.Optimizer" title="mxnet.optimizer.Optimizer"><code class="xref py py-class docutils literal"><span class="pre">Optimizer</span></code></a>.</p> <table class="docutils field-list" frame="void" rules="none"> diff --git a/versions/0.12.1/faq/develop_and_hack.html b/versions/0.12.1/faq/develop_and_hack.html index 3380cbf1..c156f09a 100644 --- a/versions/0.12.1/faq/develop_and_hack.html +++ b/versions/0.12.1/faq/develop_and_hack.html @@ -207,7 +207,6 @@ <h1 id="logo-wrap"> <div class="toctree-wrapper compound"> <ul> <li class="toctree-l1"><a class="reference internal" href="new_op.html">Create new operators</a></li> -<li class="toctree-l1"><a class="reference internal" href="torch.html">Use Torch from MXNet</a></li> <li class="toctree-l1"><a class="reference internal" href="env_var.html">Set environment variables of MXNet</a></li> </ul> </div> diff --git a/versions/0.12.1/faq/index.html b/versions/0.12.1/faq/index.html index a500ff30..b44be604 100644 --- a/versions/0.12.1/faq/index.html +++ b/versions/0.12.1/faq/index.html @@ -225,7 +225,6 @@ <h1 id="logo-wrap"> <li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/add_op_in_backend.html";>How do I implement operators in MXNet backend?</a></li> <li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/new_op.html";>How do I create new operators in MXNet?</a></li> <li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/env_var.html";>How do I set MXNet?s environmental variables?</a></li> -<li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/torch.html";>How do I use MXNet as a front end for Torch?</a></li> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="#questions-about-using-mxnet">Questions about Using MXNet</a></li> @@ -291,7 +290,6 @@ <h1 id="logo-wrap"> <li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/add_op_in_backend.html";>How do I implement operators in MXNet backend?</a></li> <li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/new_op.html";>How do I create new operators in MXNet?</a></li> <li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/env_var.html";>How do I set MXNet?s environmental variables?</a></li> -<li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/torch.html";>How do I use MXNet as a front end for Torch?</a></li> </ul> </div> </div> diff --git a/versions/0.12.1/how_to/develop_and_hack.html b/versions/0.12.1/how_to/develop_and_hack.html index abb1e38c..ffe4f1b5 100644 --- a/versions/0.12.1/how_to/develop_and_hack.html +++ b/versions/0.12.1/how_to/develop_and_hack.html @@ -169,7 +169,6 @@ <h1 id="logo-wrap"> <div class="toctree-wrapper compound"> <ul> <li class="toctree-l1"><a class="reference internal" href="new_op.html">Create new operators</a></li> -<li class="toctree-l1"><a class="reference internal" href="torch.html">Use Torch from MXNet</a></li> <li class="toctree-l1"><a class="reference internal" href="env_var.html">Set environment variables of MXNet</a></li> </ul> </div> diff --git a/versions/0.12.1/how_to/index.html b/versions/0.12.1/how_to/index.html index c7b49a4d..ac836950 100644 --- a/versions/0.12.1/how_to/index.html +++ b/versions/0.12.1/how_to/index.html @@ -188,7 +188,6 @@ <h1 id="logo-wrap"> <li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/community/contribute.html";>How do I contribute a patch to MXNet?</a></li> <li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/new_op.html";>How do I create new operators in MXNet?</a></li> <li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/env_var.html";>How do I set MXNet?s environmental variables?</a></li> -<li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/torch.html";>How do I use MXNet as a front end for Torch?</a></li> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="#questions-about-using-mxnet">Questions about Using MXNet</a></li> @@ -251,7 +250,6 @@ <h1 id="logo-wrap"> <li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/community/contribute.html";>How do I contribute a patch to MXNet?</a></li> <li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/new_op.html";>How do I create new operators in MXNet?</a></li> <li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/env_var.html";>How do I set MXNet?s environmental variables?</a></li> -<li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/how_to/torch.html";>How do I use MXNet as a front end for Torch?</a></li> </ul> </div> </div> diff --git a/versions/master/_modules/mxnet/optimizer.html b/versions/master/_modules/mxnet/optimizer.html index daee3d9f..aca10f1f 100644 --- a/versions/master/_modules/mxnet/optimizer.html +++ b/versions/master/_modules/mxnet/optimizer.html @@ -1381,7 +1381,7 @@ <h1>Source code for mxnet.optimizer</h1><div class="highlight"><pre> <span class="sd"> Much like Adam is essentially RMSprop with momentum,</span> <span class="sd"> Nadam is Adam RMSprop with Nesterov momentum available</span> -<span class="sd"> at http://cs229.stanford.edu/proj2015/054_report.pdf.</span> +<span class="sd"> at https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ.</span> <span class="sd"> This optimizer accepts the following parameters in addition to those accepted</span> <span class="sd"> by :class:`.Optimizer`.</span> diff --git a/versions/master/api/python/model.html b/versions/master/api/python/model.html index 496a3b98..40404c7c 100644 --- a/versions/master/api/python/model.html +++ b/versions/master/api/python/model.html @@ -2238,7 +2238,7 @@ <h1 id="logo-wrap"> <dd><p>The Nesterov Adam optimizer.</p> <p>Much like Adam is essentially RMSprop with momentum, Nadam is Adam RMSprop with Nesterov momentum available -at <a class="reference external" href="http://cs229.stanford.edu/proj2015/054_report.pdf";>http://cs229.stanford.edu/proj2015/054_report.pdf</a>.</p> +at <a class="reference external" href="https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ";>https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ</a>.</p> <p>This optimizer accepts the following parameters in addition to those accepted by <a class="reference internal" href="optimization/optimization.html#mxnet.optimizer.Optimizer" title="mxnet.optimizer.Optimizer"><code class="xref py py-class docutils literal"><span class="pre">Optimizer</span></code></a>.</p> <table class="docutils field-list" frame="void" rules="none"> diff --git a/versions/master/api/python/optimization.html b/versions/master/api/python/optimization.html index d0a5c530..5fd057d6 100644 --- a/versions/master/api/python/optimization.html +++ b/versions/master/api/python/optimization.html @@ -863,7 +863,7 @@ <h1 id="logo-wrap"> <dd><p>The Nesterov Adam optimizer.</p> <p>Much like Adam is essentially RMSprop with momentum, Nadam is Adam RMSprop with Nesterov momentum available -at <a class="reference external" href="http://cs229.stanford.edu/proj2015/054_report.pdf";>http://cs229.stanford.edu/proj2015/054_report.pdf</a>.</p> +at <a class="reference external" href="https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ";>https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ</a>.</p> <p>This optimizer accepts the following parameters in addition to those accepted by <a class="reference internal" href="#mxnet.optimizer.Optimizer" title="mxnet.optimizer.Optimizer"><code class="xref py py-class docutils literal"><span class="pre">Optimizer</span></code></a>.</p> <table class="docutils field-list" frame="void" rules="none"> diff --git a/versions/master/api/python/optimization/optimization.html b/versions/master/api/python/optimization/optimization.html index 4683430b..4abd9b57 100644 --- a/versions/master/api/python/optimization/optimization.html +++ b/versions/master/api/python/optimization/optimization.html @@ -1029,7 +1029,7 @@ <h1 id="logo-wrap"> <dd><p>The Nesterov Adam optimizer.</p> <p>Much like Adam is essentially RMSprop with momentum, Nadam is Adam RMSprop with Nesterov momentum available -at <a class="reference external" href="http://cs229.stanford.edu/proj2015/054_report.pdf";>http://cs229.stanford.edu/proj2015/054_report.pdf</a>.</p> +at <a class="reference external" href="https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ";>https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ</a>.</p> <p>This optimizer accepts the following parameters in addition to those accepted by <a class="reference internal" href="#mxnet.optimizer.Optimizer" title="mxnet.optimizer.Optimizer"><code class="xref py py-class docutils literal"><span class="pre">Optimizer</span></code></a>.</p> <table class="docutils field-list" frame="void" rules="none"> diff --git a/versions/master/how_to/develop_and_hack.html b/versions/master/how_to/develop_and_hack.html index 3b09fd27..15973515 100644 --- a/versions/master/how_to/develop_and_hack.html +++ b/versions/master/how_to/develop_and_hack.html @@ -198,7 +198,6 @@ <h1 id="logo-wrap"> <div class="toctree-wrapper compound"> <ul> <li class="toctree-l1"><a class="reference internal" href="new_op.html">Create new operators</a></li> -<li class="toctree-l1"><a class="reference internal" href="torch.html">Use Torch from MXNet</a></li> <li class="toctree-l1"><a class="reference internal" href="env_var.html">Set environment variables of MXNet</a></li> </ul> </div> diff --git a/versions/master/how_to/index.html b/versions/master/how_to/index.html index 9720ea4a..eba17956 100644 --- a/versions/master/how_to/index.html +++ b/versions/master/how_to/index.html @@ -215,7 +215,6 @@ <h1 id="logo-wrap"> <li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/versions/master/community/contribute.html";>How do I contribute a patch to MXNet?</a></li> <li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/versions/master/how_to/new_op.html";>How do I create new operators in MXNet?</a></li> <li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/versions/master/how_to/env_var.html";>How do I set MXNet?s environmental variables?</a></li> -<li class="toctree-l3"><a class="reference external" href="https://mxnet.incubator.apache.org/versions/master/how_to/torch.html";>How do I use MXNet as a front end for Torch?</a></li> </ul> </li> <li class="toctree-l2"><a 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